rob leathern - facebook to display: retargeting your audience
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Confidential
Retargeting Audiences Across Facebook and DisplayAFExpo - June 2011
Confidential
Confidential
The Trade-off
Keep Users Inside Facebook or Outside of Facebook?
FacebookFacebook
RetargetingRetargeting
LookalikesLookalikes
Fans + Friends of
Fans
XA.net is the first company to operatereal-time bidding audience-targetedcampaigns (including retargeting) andalso be a Facebook Ads API approvedvendor and social media expert
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Web Retargeting
Every Site Visit Should Initiate Retargeting Pixel(s)
Google AdMeld
AdBriteYahoo!
Rubicon ContextWeb
Landing Page 1
Landing Page 2
Landing Page 3
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XA.net on Facebook
Optim.al: Integrated Multivariate Facebook Ad Buying
4
Multivariate text ad optimization
XA.net built one of the first direct Facebook Ads API integrations.
Platform creates evolutionary variations of your ad components, to find top performing “DNA” / variations.
Multivariate testing can produce the optimal ad combinations, often yielding 7x lift or more in performance.
Proprietary methodology tests more variants with fewer ads (3,888 ads compressed to <20).
72 text/image variationsX
9 geo/interest combinationsx
3 different age rangesx
Male or Female=
3,888 possible combinations
Only 18 test ads
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XA.net Technology
Real-time Bidding and Audience Infrastructure• Real-time bidding (RTB) is ad inventory being put out to “bid” by a bidding server to
a number of client servers:
SystemA
Bid requests
BidderServers
Each bid request has basic data about theimpression and user about to see it:-IP address-Unique UserID-URL-Referring URL etc….
The bidder server looks at the data and decides whether to bid on the impression, and how much:Often this is a static “rules-based” decision
If the bidder wins the impression auction, their creative is sent and displayed to the user
User
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XA.net Technology
XA.net Approach to Audience-level Infrastructure• Audience-level real-time infrastructure is useful not just for making media buying
decisions, but for optimizing throughout the funnel• Think of individual creatives and landing pages just as other pieces of media where
audience- and context-based decisions are being made in real-time:
Media
Creative
Lander
18-24 25-34 Clicker
Each product has its own modeland “likely conversion tree”
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XA.net Technology
Impressions are Not a Commodity: Sessions Matter
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$3.80$3.80
$3.05$3.05
$2.50$2.50
$2.10$2.10
$1.50$1.50
1 2 3 4 5+
1 2 3 4 5+Purchase Direct Direct Direct Mix Exchange(s)
CTR 0.31% 0.28% 0.24% 0.22% 0.16%
eCPC $0.32 $0.36 $0.42 $0.45 $0.63
Figures based on actual publisher/exchange observed data (2009-2010)
Impressions at different points in the session queue usually have differing performance characteristics
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XA.net Technology
Evolutionary Optimization: Proven Success
‐100%
0%
100%
200%
300%
400%
500%
1-Mar 4-Mar 7-Mar 10-Mar 13-Mar 16-Mar 19-Mar 22-Mar 25-Mar 28-Mar
Ad V
aria
tion
CPC Down 50%
CTR Up 400%
• New generations of ad variants are built from the strongest of the previous generation, driving performance and lowering cost.
Source: XA.net Customer (2011)
3rdGe
nera
tion
3rdGe
nera
tion
2ndGe
nera
tion
2ndGe
nera
tion
1stGe
nera
tion
1stGe
nera
tion
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XA.net Technology
Case Study: Evolutionary Optimization
Source: XA.net Customer (2011)
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Creative Learnings on Facebook Translate to Display
• Large advertiser’s best performing image on Facebook Ads worked very well on general display. Facebook ads were much cheaper to test (less design costs!).
• Copy and headline don’t translate as effectively – but images are very powerful
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XA.net Audience Data
How To Use Social Data (Example): Brand X on FB
Strong WeakDelaware, New Jersey, RhodeIsland, West Virginia, Kentucky
Utah, Idaho, Minnesota, Hawaii, Montana
129
100
63
Index
Source: optim.al, Facebook n=3,874,140 US people interested in Brand
Brand wanted to understand overlap between markets wherecertain affiliates have coverageand fans of the series.
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XA.net Audience Data
Brand X on Facebook: Sample Data Detail
Facebook Users Brand Fans % Fans Index
All US 142,537,020 3,874,140 2.72% 100
Delaware 375,260 13,180 3.5% 129
Virginia 3,362,380 102,500 3.0% 112
California 18,747,780 409,020 2.2% 80
Jacksonville, FL 532,540 20,500 3.9% 142
Louisville, KY 531,080 17,180 3.2% 119
Indianapolis, IN 716,420 16,160 2.3% 83
Source: optim.al, Facebook n=3,874,140 US people interested in Brand
Cities
States
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Building a Portfolio Approach
Audience Analysis: Understanding Impact by Demo• Social data needs to be looked at in the right context: Example data: Male, 19-24, US• Sample, test & minimize cannibalization of “earned media” efforts
Mafia Wars56.8%
Mafia Wars56.8%
Cityville11.6%
Cityville11.6%
Frontierville19.9%
Frontierville19.9%
1.1%
2.2%
2.1%
6.2%
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Turning Data Action
Starbucks Fans Younger than Dunkin’ Donuts
- 50 100 150 200 250
1315171921232527293133353739414345474951535557596163
StarbucksDunkin' Donuts
Indexed to 100 (vs. US Facebook population)
Average ages:
US (Facebook): 31.4
Starbucks: 24.6
Dunkin’ Donuts: 26.4
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Audience Similarity
Don’t Buy Data Yet: First Determine Your Best Users
23.69%
39.89%
10.43%
20.37%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Seg#
041
Seg#
071
Seg#
145
Seg#
170
Seg#
038
Seg#
020
Seg#
119
Seg#
150
Seg#
082
Seg#
132
Seg#
070
Seg#
059
Seg#
124
Seg#
022
Seg#
094
Seg#
046
Seg#
034
Seg#
030
Seg#
101
Seg#
126
Seg#
129
Seg#
003
Seg#
025
Seg#
108
Seg#
159
Seg#
067
Seg#
005
Seg#
166
Seg#
092
Seg#
050
Seg#
024
Seg#
118
Seg#
104
Seg#
165
Seg#
053
Seg#
045
Seg#
151
Seg#
114
Seg#
008
Seg#
160
Seg#
154
Seg#
103
Seg#
091
US PopulationProduct Buyers
Source: XA.net Analysis, 10/2010, n=5302 Consumer Product online buyers
% of conversions
20.4% of the audience = 39.9% of client’s buyers
Cumulative distribution by segment
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9.99%
20.00%21.52%
40.35%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Seg#
071
Seg#
145
Seg#
020
Seg#
144
Seg#
141
Seg#
130
Seg#
124
Seg#
123
Seg#
058
Seg#
059
Seg#
121
Seg#
085
Seg#
048
Seg#
030
Seg#
135
Seg#
017
Seg#
127
Seg#
025
Seg#
005
Seg#
100
Seg#
101
Seg#
126
Seg#
073
Seg#
009
Seg#
047
Seg#
050
Seg#
166
Seg#
029
Seg#
054
Seg#
113
Seg#
161
Seg#
075
Seg#
152
Seg#
055
Seg#
057
US PopulationSocial game ad clickers
Source: XA.net Analysis, 1/2011, n=1,013,271 social gaming ad clickers
Audience Similarity
Server-Side Data Integration Allows Targeted Buys
% of ad clickers
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Sponsored Stories are Complicated • Page like story
Facebook description: When people like your Page, their friends see a story about it• Trigger: Page Like by User
• Audience: Friends of Fans (of Page)
• Value: Acquiring new Fans
• Page post story Facebook description: When you post an update to your Page, your fans see a story about it• Trigger: Page Post by Admin
• Audience: Existing Fans (of Page)
• Value: Re-engaging Fans, not effective for acquiring new Fans
• Page post like story Facebook description: When people like your Page post, their friends see a story about it• Trigger: Page Post Like by User (includes new updates, photos, videos)
• Audience: Friends of Fans (of Post)
• Value: Unclear - may not be effective for acquiring new Fans (of Page)
• Check-in story Facebook description: When people check-in to your business using Facebook Places, their friends see a story about it• Trigger: Check-in by User
• Audience: Friends of Users (who've checked in)
• Value: Acquiring new Fans
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Sponsored Stories are Complicated (cont’d) • App used & game played story
Facebook description: When people have recently used your App or played your game, their friends see a story about it• Trigger: App Install / Interaction by User
• Audience: Friends of Users
• Value: Acquiring new Users
• App share story Facebook description: When people share from your App, their friends see a story about it• Trigger: Shared Interaction w/App by User
• Audience: Friends of Users
• Value: Acquiring new Users
• Domain story Facebook description: When people like or share information about your Domain, their friends see a story about it• Trigger: Interaction with Facebook content on a 3rd party site (e.g. Like or Share button) by User
• Audience: Friends of Fans/Users
• Value: Acquiring new Fans/Users
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$0.79
$0.60
$0.50 $0.48 $0.47 $0.49 $0.46 $0.44
$‐
$0.10
$0.20
$0.30
$0.40
$0.50
$0.60
$0.70
$0.80
$0.90
‐
5,000
10,000
15,000
20,000
25,000
6/15/11 6/16/11 6/17/11 6/18/11 6/19/11 6/20/11 6/21/11 6/22/11
The Friend of My Fan is My FriendDecreasing Cost of Fans Discovered‐>Acquired through "Ads with Friends"
Fans Cost‐per‐Fan
But Can Be Very Effective and Improve Quickly
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Testing is Key: Facebook Changes Rapidly• Consider how frequently you are engaging fans on your pages – possible
cannibalization of paid vs. earned media efforts• Do you have an ecommerce site, trying to capture a transaction directly?• How hard is it to find your audience (pet owners, Cisco employees?)• How likely are your fans to be customers; and how likely are friends of fans to
become fans and become customers• What is the legacy of your fan base – did you “buy” a lot of untargeted fans?• How viral is your product or offer?• Can you track multiple conversion events including inside of Facebook apps• Look at lead generation such as email gathering in addition to fan capture
•In the future, lines between what is/not social will be more blurred but testing will always be vital
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Thanks and Contact Us!Rob Leathern (rob@xa.net) / Founder and CEOSasha Ziman (sasha@xa.net) / Director of Sales
http://be.optim.al/about
http://the.optim.al - our blog with data insights!
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